| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | | totalTags | 6 | | adverbTagCount | 0 | | adverbTags | (empty) | | dialogueSentences | 11 | | tagDensity | 0.545 | | leniency | 1 | | rawRatio | 0 | | effectiveRatio | 0 | |
| 89.33% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 937 | | totalAiIsmAdverbs | 2 | | found | | 0 | | | 1 | | adverb | "barely above a whisper" | | count | 1 |
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| | highlights | | 0 | "truly" | | 1 | "barely above a whisper" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (16 tracked, −20% each) | | codexExemptions | | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 0.00% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 937 | | totalAiIsms | 19 | | found | | 0 | | | 1 | | | 2 | | word | "skipped a beat" | | count | 1 |
| | 3 | | | 4 | | | 5 | | | 6 | | | 7 | | | 8 | | | 9 | | | 10 | | | 11 | | | 12 | |
| | highlights | | 0 | "navigated" | | 1 | "unspoken" | | 2 | "skipped a beat" | | 3 | "racing" | | 4 | "scanned" | | 5 | "tension" | | 6 | "palpable" | | 7 | "echo" | | 8 | "weight" | | 9 | "whisper" | | 10 | "sense of" | | 11 | "pang" | | 12 | "reminder" |
| |
| 66.67% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 2 | | maxInWindow | 2 | | found | | 0 | | label | "hung in the air" | | count | 1 |
| | 1 | | label | "flicker of emotion" | | count | 1 |
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| | highlights | | 0 | "hung in the air" | | 1 | "a flash of recognition" |
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| 92.32% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 2 | | narrationSentences | 51 | | matches | | 0 | "felt a jolt" | | 1 | "a pang of sadness" |
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| 30.81% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 3 | | narrationSentences | 51 | | filterMatches | | | hedgeMatches | | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 56 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | maxSentenceWordsSeen | 31 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 0 | | markdownWords | 0 | | totalWords | 933 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 7 | | unquotedAttributions | 0 | | matches | (empty) | |
| 0.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 49 | | wordCount | 830 | | uniqueNames | 10 | | maxNameDensity | 3.13 | | worstName | "Rory" | | maxWindowNameDensity | 5.5 | | worstWindowName | "Rory" | | discoveredNames | | Raven | 1 | | Nest | 1 | | Carter | 1 | | Silas | 1 | | Blackwood | 1 | | Rory | 26 | | Eva | 15 | | Cardiff | 1 | | Evan | 1 | | London | 1 |
| | persons | | 0 | "Raven" | | 1 | "Nest" | | 2 | "Carter" | | 3 | "Silas" | | 4 | "Blackwood" | | 5 | "Rory" | | 6 | "Eva" | | 7 | "Evan" |
| | places | | | globalScore | 0 | | windowScore | 0 | |
| 97.92% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 48 | | glossingSentenceCount | 1 | | matches | | |
| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 933 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 56 | | matches | (empty) | |
| 66.15% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 22 | | mean | 42.41 | | std | 16.18 | | cv | 0.382 | | sampleLengths | | 0 | 66 | | 1 | 21 | | 2 | 51 | | 3 | 56 | | 4 | 54 | | 5 | 19 | | 6 | 26 | | 7 | 33 | | 8 | 46 | | 9 | 57 | | 10 | 25 | | 11 | 33 | | 12 | 28 | | 13 | 47 | | 14 | 44 | | 15 | 39 | | 16 | 15 | | 17 | 67 | | 18 | 45 | | 19 | 59 | | 20 | 31 | | 21 | 71 |
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| 77.74% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 4 | | totalSentences | 51 | | matches | | 0 | "been honed" | | 1 | "been honed" | | 2 | "was gone" | | 3 | "was gone" |
| |
| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 1 | | totalVerbs | 139 | | matches | | |
| 100.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 0 | | semicolonCount | 0 | | flaggedSentences | 0 | | totalSentences | 56 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 834 | | adjectiveStacks | 0 | | stackExamples | (empty) | | adverbCount | 23 | | adverbRatio | 0.027577937649880094 | | lyAdverbCount | 7 | | lyAdverbRatio | 0.008393285371702638 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 56 | | echoCount | 0 | | echoWords | (empty) | |
| 86.76% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 56 | | mean | 16.66 | | std | 6.11 | | cv | 0.367 | | sampleLengths | | 0 | 27 | | 1 | 19 | | 2 | 20 | | 3 | 21 | | 4 | 19 | | 5 | 18 | | 6 | 14 | | 7 | 16 | | 8 | 21 | | 9 | 19 | | 10 | 14 | | 11 | 23 | | 12 | 17 | | 13 | 19 | | 14 | 19 | | 15 | 7 | | 16 | 20 | | 17 | 13 | | 18 | 23 | | 19 | 13 | | 20 | 2 | | 21 | 8 | | 22 | 10 | | 23 | 22 | | 24 | 19 | | 25 | 5 | | 26 | 1 | | 27 | 11 | | 28 | 14 | | 29 | 18 | | 30 | 15 | | 31 | 11 | | 32 | 17 | | 33 | 17 | | 34 | 17 | | 35 | 13 | | 36 | 17 | | 37 | 27 | | 38 | 13 | | 39 | 26 | | 40 | 15 | | 41 | 26 | | 42 | 19 | | 43 | 22 | | 44 | 16 | | 45 | 13 | | 46 | 16 | | 47 | 17 | | 48 | 13 | | 49 | 29 |
| |
| 61.90% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 2 | | diversityRatio | 0.39285714285714285 | | totalSentences | 56 | | uniqueOpeners | 22 | |
| 0.00% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 100.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 11 | | totalSentences | 49 | | matches | | 0 | "She made her way to" | | 1 | "she asked, running a hand" | | 2 | "His grey-streaked auburn hair and" | | 3 | "It had been years since" | | 4 | "she teased, snagging a stool" | | 5 | "she admitted, feeling a little" | | 6 | "she asked, her voice barely" | | 7 | "She opened her mouth to" | | 8 | "They'd been friends since childhood," | | 9 | "She knew, in that moment," | | 10 | "She knew, in that moment," |
| | ratio | 0.224 | |
| 100.00% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 33 | | totalSentences | 49 | | matches | | 0 | "The sign above the entrance" | | 1 | "Aurora Carter navigated the crowded" | | 2 | "She made her way to" | | 3 | "she asked, running a hand" | | 4 | "Silas Blackwood looked up from" | | 5 | "His grey-streaked auburn hair and" | | 6 | "Rory's heart skipped a beat" | | 7 | "The woman's eyes scanned the" | | 8 | "A slow smile spread across" | | 9 | "Rory's voice caught on the" | | 10 | "Eva's smile faltered for an" | | 11 | "Rory's initial stiffness melted beneath" | | 12 | "The realization hit Rory like" | | 13 | "It had been years since" | | 14 | "Rory had assumed she'd never" | | 15 | "Eva's eyes sparkled with amusement" | | 16 | "she teased, snagging a stool" | | 17 | "Rory shook her head, her" | | 18 | "she admitted, feeling a little" | | 19 | "Eva's gaze softened, her voice" |
| | ratio | 0.673 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 49 | | matches | (empty) | | ratio | 0 | |
| 90.59% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 41 | | technicalSentenceCount | 3 | | matches | | 0 | "Tall, with a striking bright blue gaze and shoulder-length black hair, she moved with a confident air that drew the eye." | | 1 | "Rory shook her head, her eyes drifting to the barkeep as he expertly juggling three drinks at once." | | 2 | "The girl she'd known was gone, replaced by a confident, driven woman who seemed to have left Rory's small world far behind." |
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| 0.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 6 | | uselessAdditionCount | 2 | | matches | | 0 | "Rory's voice caught on, her hand faltering as she reached for her drink" | | 1 | "she asked, her voice barely above a whisper" |
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| 0.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | | totalTags | 4 | | fancyCount | 2 | | fancyTags | | 0 | "she teased (tease)" | | 1 | "she admitted (admit)" |
| | dialogueSentences | 11 | | tagDensity | 0.364 | | leniency | 0.727 | | rawRatio | 0.5 | | effectiveRatio | 0.364 | |